Distortion-Aware Loop Filtering of Intra 360^o Video Coding with Equirectangular Projection

Combining Progressive Rethinking and Collaborative Learning: A Deep Framework for In-Loop Filtering

In this paper, we aim to address issues of (1) joint spatial-temporal modeling and (2) side information injection for deep-learning based in-loop filter. For (1), we design a deep network with both progressive rethinking and collaborative learning mechanisms to improve quality of the reconstructed intra-frames and inter-frames, respectively. For intra coding, a Progressive Rethinking Network (PRN) is designed to simulate the human decision mechanism for effective spatial modeling. Our designed block introduces an additional inter-block connection to bypass a high-dimensional informative featur…

Multi-Projection Fusion and Refinement Network for Salient Object Detection in 360° Omnidirectional Image

Salient object detection (SOD) aims to determine the most visually attractive objects in an image. With the development of virtual reality technology, 360° omnidirectional image has been widely used, but the SOD task in 360° omnidirectional image is seldom studied due to its severe distortions and complex scenes. In this paper, we propose a Multi-Projection Fusion and Refinement Network (MPFR-Net) to detect the salient objects in 360° omnidirectional image. Different from the existing methods, the equirectangular projection image and four corresponding cube-unfolding images are embedded into t…

Synthetic Augmentation and Feature-based Filtering for Improved Cervical Histopathology Image Classification

Cervical intraepithelial neoplasia (CIN) grade of histopathology images is a crucial indicator in cervical biopsy results. Accurate CIN grading of epithelium regions helps pathologists with precancerous lesion diagnosis and treatment planning. Although an automated CIN grading system has been desired, supervised training of such a system would require a large amount of expert annotations, which are expensive and time-consuming to collect. In this paper, we investigate the CIN grade classification problem on segmented epithelium patches. We propose to use conditional Generative Adversarial Netw…

Both Style and Distortion Matter: Dual-Path Unsupervised Domain Adaptation for Panoramic Semantic Segmentation

The ability of scene understanding has sparked active research for panoramic image semantic segmentation. However, the performance is hampered by distortion of the equirectangular projection (ERP) and a lack of pixel-wise annotations. For this reason, some works treat the ERP and pinhole images equally and transfer knowledge from the pinhole to ERP images via unsupervised domain adaptation (UDA). However, they fail to handle the domain gaps caused by: 1) the inherent differences between camera sensors and captured scenes; 2) the distinct image formats (e.g., ERP and pinhole images). In this pa…

基于训练查找表的环内滤波

In-Loop Filtering via Trained Look-Up Tables

针对基于神经网络的环内滤波复杂度高、难落地的问题，提出基于训练查找表的高效环内滤波方案，通过缓存DNN输出、增强索引等机制降低复杂度，在VVC参考软件中实现了可观编码增益与极低的存储、计算开销。

ResMatch：用于局部特征匹配的残差注意力学习

ResMatch: Residual Attention Learning for Local Feature Matching

本文从传统匹配与过滤视角重新设计交叉/自注意力，提出残差注意力学习网络 ResMatch 及稀疏版本 sResMatch，并在多类视觉任务中验证其优势。